Files
xau-traderbot/main.py
T
Mazonia e8b349ccf0 feat: complete AI model training pipeline, MT5 live order execution, and scheduled pending orders
- Implemented scripts/train_ai.py for institutional XGBoost training on MT5 historical candles
- Integrated 46 multi-indicator features, TimeSeriesSplit validation, and feature importance drivers
- Added --train-only and improved --train in main.py
- Enabled MT5 AutoTrading configuration ([Experts] AllowLiveTrading=1)
- Added send_pending_order and cancel_order to MT5Connector (BUY_LIMIT, SELL_LIMIT, BUY_STOP, SELL_STOP)
- Added automatic 12-hour periodic model retraining job in BotScheduler and TradingBot
- Updated Telegram Command Center with MT5 standalone fallback and pending order telemetry
- Placed live test BUY market trade and scheduled BUY_LIMIT order on XAUUSD
2026-09-21 10:13:52 +00:00

203 lines
5.3 KiB
Python

"""
XAUUSD AI Trading Bot — Entry Point
Usage:
python main.py # Start the trading bot
python main.py --train # Train AI models first, then start
python main.py --backtest # Run backtesting only
python main.py --dashboard # Start web dashboard only
"""
import argparse
import asyncio
import sys
from loguru import logger
def parse_args():
parser = argparse.ArgumentParser(
description="XAUUSD AI Trading Bot",
formatter_class=argparse.RawDescriptionHelpFormatter,
)
parser.add_argument(
"--train",
action="store_true",
help="Train AI models before starting the bot",
)
parser.add_argument(
"--train-only",
action="store_true",
help="Train AI models and exit without starting the bot",
)
parser.add_argument(
"--backtest",
action="store_true",
help="Run backtesting only (no live trading)",
)
parser.add_argument(
"--dashboard",
action="store_true",
help="Start web dashboard only (no trading)",
)
parser.add_argument(
"--telegram",
action="store_true",
help="Start interactive Telegram Command Center only",
)
parser.add_argument(
"--demo",
action="store_true",
default=True,
help="Run in demo mode (default: True)",
)
return parser.parse_args()
async def train_models():
"""Train AI models using historical data."""
from core.mt5_connector import MT5Connector
from ai.price_predictor import PricePredictor
from ai.signal_classifier import SignalClassifier
logger.info("=" * 60)
logger.info(" Training AI Models")
logger.info("=" * 60)
mt5 = MT5Connector()
if not mt5.connect():
logger.error("Cannot connect to MT5 for training data")
return
try:
from scripts.train_ai import run_training_pipeline
run_training_pipeline(timeframe="M15", count=3000)
# Optional LSTM if TensorFlow is installed
try:
import tensorflow
df = mt5.get_rates(timeframe="H1", count=2000)
if df is not None:
lstm = PricePredictor()
lstm.train(df, epochs=10)
except Exception:
pass
logger.success("✅ AI models trained and ready for live execution")
finally:
mt5.disconnect()
def start_dashboard():
"""Start the web dashboard server."""
import uvicorn
from config.settings import get_settings
settings = get_settings()
logger.info(f"Starting dashboard on http://{settings.dashboard.host}:{settings.dashboard.port}")
uvicorn.run(
"dashboard.app:app",
host=settings.dashboard.host,
port=settings.dashboard.port,
reload=False,
)
def run_telegram():
"""Run interactive Telegram Command Center in standalone mode with native long-polling."""
from notifications.telegram_bot import TelegramNotifier
from core.mt5_connector import MT5Connector
logger.info("=" * 60)
logger.info(" Starting Telegram Command Center (Standalone Mode)")
logger.info("=" * 60)
mt5 = MT5Connector()
mt5.connect(max_retries=1, retry_delay=1)
from strategies.regime_detector import RegimeDetector
from analysis.technical import TechnicalAnalyzer
class StandaloneBot:
def __init__(self, mt5_conn):
self.mt5 = mt5_conn
self.regime_detector = RegimeDetector()
self.technical = TechnicalAnalyzer()
self._last_regime = None
self._trading_paused = False
bot_wrapper = StandaloneBot(mt5)
notifier = TelegramNotifier(bot_instance=bot_wrapper)
try:
notifier.run_standalone()
except KeyboardInterrupt:
logger.info("Telegram Bot terminated by user")
def run_backtest():
"""Run historical backtesting simulation."""
from backtesting.backtester import Backtester
from core.mt5_connector import MT5Connector
logger.info("=" * 60)
logger.info(" Starting XAUUSD Multi-Strategy Backtester")
logger.info("=" * 60)
bt = Backtester(initial_balance=10_000.0, lot_size=0.02)
df = None
# Try fetching real data from MT5 first if available
try:
mt5 = MT5Connector()
if mt5.connect(max_retries=1, retry_delay=1):
logger.info("Fetching real historical H1 data from MT5...")
df = mt5.get_rates(timeframe="H1", count=2000)
mt5.disconnect()
except Exception as e:
logger.debug(f"MT5 historical data fetch skipped: {e}")
if df is None or len(df) < 500:
logger.info("Using high-fidelity synthetic Gold benchmark data (1,500 candles)...")
df = bt.generate_benchmark_data(bars=1500)
bt.run(df)
def main():
args = parse_args()
if args.dashboard:
start_dashboard()
return
if args.telegram:
run_telegram()
return
if args.backtest:
run_backtest()
return
if args.train_only:
asyncio.run(train_models())
return
if args.train:
asyncio.run(train_models())
# Start the live trading bot
from core.bot import TradingBot
bot = TradingBot()
asyncio.run(bot.start())
if __name__ == "__main__":
try:
main()
except KeyboardInterrupt:
logger.info("Bot terminated by user")
sys.exit(0)